Sr. Security Engineer - FRM
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Before you apply
LocationBengaluru
SenioritySenior
Experience4–7 yrs
DepartmentEngineering
Company size51–200 people
PostedOct 13, 2026 · 3w ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
4–7 years of experience in Fraud Risk Management, Trust & Safety, or Risk Engineering
Hands-on experience building or operating real-time fraud detection and transaction monitoring systems
Strong understanding of risk scoring, rules engines, and/or ML-based fraud detection approaches
Experience working with payment flows, UPI, wallets, or similar transaction-heavy systems
Familiarity with regulatory requirements around fraud and risk controls — NPCI, RBI, sanctions/watchlist screening, suspicious-transaction reporting, and comparable regimes
Proficiency in Python or a similar language; comfortable working with SQL and large transactional datasets
Strong analytical mindset, with the ability to translate emerging fraud patterns and typologies into actionable detection logic
Comfortable owning a control that only works if someone actually works it — the review queue and escalation path are real from the day you’re behind them
Experience with UPI/TPAP ecosystems or NPCI-regulated payment products is a plus
Experience with case management tools and fraud investigation workflows is a plus
Exposure to machine learning-based risk models in production, including model governance and drift monitoring, is a plus
Prior experience supporting statutory or regulatory audits related to fraud or risk controls is a plus
Skills
Python
SQL
ML
Key Responsibilities :
•
4–7 years of experience in Fraud Risk Management, Trust & Safety, or Risk Engineering, ideally in fintech, payments, or banking
•
Hands-on experience building or operating real-time fraud detection and transaction monitoring systems
•
Strong understanding of risk scoring, rules engines, and/or ML-based fraud detection approaches
•
Experience working with payment flows, UPI, wallets, or similar transaction-heavy systems
•
Familiarity with regulatory requirements around fraud and risk controls — NPCI, RBI, sanctions/watchlist screening, suspicious-transaction reporting, and comparable regimes
•
Proficiency in Python or a similar language; comfortable working with SQL and large transactional datasets
•
Strong analytical mindset, with the ability to translate emerging fraud patterns and typologies into actionable detection logic
•
Comfortable owning a control that only works if someone actually works it — the review queue and escalation path are real from the day you’re behind them
•
Experience with UPI/TPAP ecosystems or NPCI-regulated payment products is a plus
•
Experience with case management tools and fraud investigation workflows is a plus
•
Exposure to machine learning-based risk models in production, including model governance and drift monitoring, is a plus
•
Prior experience supporting statutory or regulatory audits related to fraud or risk controls is a plus